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Web Mining.

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Presentation on theme: "Web Mining."— Presentation transcript:

1 Web Mining

2 Web Mining Web mining is the application of data mining techniques to find interesting and potentially useful knowledge from web data.

3 What is Web Data ? Web data is Web content –text,image,records,etc.
Web structure –hyperlinks,tags,etc. Web usage –http logs,app server logs,etc.

4 Web Mining Taxonomy Web-Mining Web Usage Mining Web Structured Mining
Web Content Mining

5 Web Content Mining Discovery of useful information from web contents / data / documents Web data contents: text, image, audio, video, metadata and hyperlinks

6 Web Structured Mining It deal with discovering and modeling the link structure of the web. Work has been carried out to model the web based on the topology of the hyperlinks. Helps in Discovering similarities between sites In discovering important sites for a particular topic. Discovering web communities.

7 Web Usage Mining It deals with understanding user behavior in interacting with the web or with a website. Aim To obtain information that may assist web sites for reorganization or adaptation to better suit the user.

8 To understand user’s behaviour
Clicking pattern Browsing time Transaction

9 Application Target potential customers for electronic commerce
Enhance the quality and delivery of Internet information services to the end user Improve Web server system performance Identify potential prime advertisement locations Facilitates personalization/adaptive sites Improve site design Fraud/intrusion detection Predict user’s actions (allows pre fetching)

10 Web Mining Taxonomy Application Level Logs Web-Mining Web Usage Mining
Web Structured Mining Web Content Mining Text Image Audio Video Structured Web-Server Logs Application Server Logs Document Structured Hyperlinks Intra-Document Hyperlinks Inter-Document Hyperlinks

11 Web usage mining and E-Commerce
E-commerce is the killer-application of web mining Keep former customers and attract new customers Provide better service and be more interactive Web usage mining is the best way to analyse the customer’s behaviour. Discover customers needs or interests Analyse customers behaviour

12 Pattern discovery and analysis
The KDD Process for E-commerce Action Data collection and Pre-processing Pattern discovery and analysis Reconditions Again Action Mining

13 Pattern Discovery and Analysis
Using the mining algorithms to discover the pattern Pattern Analysis To filter out uninteresting/meaningless rules or patterns from the set found in the pattern discovery phase Information filter OLAP (On-line analytical processing) Visualization Knowledge query mechanism (SQL)

14 Technologies For Web Usage Mining
Web usage mining technologies Statistical analysis Most common method, such as frequency, mean (average), median, etc. Classification Mapping a data item into one of several predefined classes Clustering To group together a set of items having similar characteristics

15 Technologies For Web Usage Mining
Association rule Can be used to relate page or product that are most often referenced or purchased together Sequential patterns A set of items is followed by another item in time-order

16 E-commerce Business Objectives
Personalization Web site personalization (content or layout) Personalized advertisement Personalized product recommendation Marketing strategy Marketing rule Changing the marketing strategy Web site design Web site evaluation Reorganize Improve the hypertext structure Optimization

17 Web usage mining for e-commerce
Many applications in different areas of E-commerce have already been proposed However, most research just focuses on the first two steps of the KDD process Data mining is meaningless if we do not take action in E-commerce

18 In the area of web usage mining for
Possible work In the area of web usage mining for E-commerce. Also in the area of web search employing Web Crawlers or algorithms like HITS (Hypertext Induced topic search), Web Warehousing etc.

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